The mechanisms underlying the specificity of the responses elicited by activation of cell surface receptors are not well understood. The pituitary gonadotropin-releasing hormone receptor (GnRHR), which mediates the biosynthesis of the gonadotropins luteinizing hormone and follicle stimulating hormone, provides a salient example of the exquisite requirements for signaling specificity between the membrane and the genome. The pattern of downstream gene responses depends on the frequency of receptor stimulation. Specific patterns of GnRHR stimulation lead to the generation of distinct transcriptional programs. For example, prolonged GnRH stimulation favor induction of the common α-gona dotropin. In contrast, a specific physiologically-relevant frequency range of receptor stimulation, on the order of one pulse/hour, preferentially induces the luteinizing hormone beta subunit (LHβ) gene (see, for example, Dalkin et al. (1989) Endocrinology 125:917-24). Whereas downstream signal transduction mediators including JNK and ERK and a number of transcription factors including Egr1, SF1 and NAB1 have been implicated in modulation of the LHβ promoter (see for example Kaiser et al. (2000) Mol. Endocrinol. 14:1235-45), the available data do not explain why the induction of LHβ requires specific patterns of GnRHR activation. Furthermore, whereas it has recently been proposed that signal transduction pathways may form complex networks that manifest emergent properties whose overall patterns of activity are relatively independent of the behavior of specific components (Bhalla et al. (1999) Science 283 381-7), heretofore there has been no methodology to specifically delineate these inter-related roles of the products of the genes comprising these complex networks. Moreover, there has been no methodology to specifically exploit the general information that can be elucidated from these complex networks.
Microarray techniques have emerged as important approaches for the simultaneous analysis of multiple gene transcripts. Microarrays have proven valuable in refining cancer classification (see, for example, Alizadeh et al. (2000) Nature 403:503-11) and for providing qualitative assessment of the global gene programs that accompany cell division, development, and the responses to specific stimuli (see, for example, Iyer et al. (1999) Science 283:381-7). However, data obtained using both commercial and custom global microarrays have been limited by the expense of the assays and by problems in quality control (Knight (2001) Nature 410:860-1). The scale of genome-wide microarrays brings several problems. One is the difficulty of quality control for both academic and commercial suppliers. Another is the increase in statistical uncertainty due to multiple hypothesis testing. For an experiment utilizing a fixed number of arrays, the statistical power of correctly assigning a gene as regulated or unregulated decreases as the size of the array increases. However the high expense of global arrays constrains the number of arrays that should be analyzed to provide statistically acceptable sensitivity and specificity.
Therefore, there is a need to provide microarrays that are constructed to contain a limited number of nucleic acids affixed to them, yet still be able to allow the accurate identification of a subset of genes that are affected by a given biological interaction. In addition, there is a need to identify the specific set of genes that play a role in the initial stages of signal transduction pathways.